- Role: Generative AI Engineer
- Location: Dallas, TX (Hybrid - 3 days onsite)
- Interview Mode: Face-to-Face Final Round (In-Person Drive)
- Dates: November 18th & 19th
- Openings: 13
- Software engineering experience with AI/ML or GenAI systems in production
- Engagement: Contract
- Design, develop, and deploy agentic AI systems leveraging LLMs and modern AI frameworks.
- Integrate GenAI models into full-stack applications and internal workflows.
- Collaborate on prompt engineering, model fine-tuning, and evaluation of generative outputs.
- Build reusable components and services for multi-agent orchestration and task automation.
- Optimize AI inference pipelines for scalability, latency, and cost efficiency.
- Participate in architectural discussions, contributing to the pod's technical roadmap.
Must Haves
- Software engineering experience with AI/ML or GenAI systems in production
- Hands-on experience with Python only for AI/ML model integration.
- Experience with LLM frameworks (LangChain, LlamaIndex is a must
- Exposure to agentic frameworks (Langgraph, AutoGen, CrewAI is a must
- Understanding of Git, CI/CD, DevOps, and production-grade GenAI deployment practices.
- Familiarity with Google Cloud Platform (GCP) - especially Vertex AI, Cloud Run, and GKE.
- Experience building AI APIs, embeddings, vector search, and integrating them into applications.
- Experience fine-tuning open-source models (LLaMA, Mistral, etc.) or working with OpenAI APIs.
- Exposure to multi-modal AI systems (text, image, or voice).
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